Cooperative problem-based learning experience and coaching strategies of engineering course

The problem-based learning (PBL) methodologies are considered adequate for core engineering courses. The integration between cooperative learning and PBL methodologies establishes an encouraging environment for the students. However, for effective implementation of cooperative problem-based learning (CPBL) environment, close supervision of students’ experiences is vital, and deficient areas are to be improved, as PBL is a dynamic process. A study was conducted for the first-year undergraduate engineering class taught under the PBL environment. The objective was to evaluate the course by the preview of students, for highlighting weak domains in the teaching methodology for future improvements. A course experience questionnaire was designed considering PBL implications, with 35 question items, and 31 responses were collected by the end of the semester. Three different analyses were performed on the collected data, i.e., descriptive statistics and Cronbach’s alpha, Student's t-test, and Pearson Chi-square test. The achieved results supported the effective adoption of the PBL system by the students. However, few areas were highlighted requiring special consideration, such as PBL workload, pressure due to extra course content, and assessment opportunities under the PBL system. It was proved that maximum students considered PBL methodologies convenient and effective for learning than the traditional learning approach

Data Processing Using Artificial Neural Networks

The artificial neural network (ANN) is a machine learning (ML) methodology that evolved and developed from the scheme of imitating the human brain. Artificial intelligence (AI) pyramid illustrates the evolution of ML approach to ANN and leading to deep learning (DL). Nowadays, researchers are very much attracted to DL processes due to its ability to overcome the selectivity-invariance problem. In this chapter, ANN has been explained by discussing the network topology and development parameters (number of nodes, number of hidden layers, learning rules and activated function). The basic concept of node and neutron has been explained, with the help of diagrams, leading to the ANN model and its operation. All the topics have been discussed in such a scheme to give the reader the basic concept and clarity in a sequential way from ANN perceptron model to deep learning models and underlying types

Impact of Zero Energy Building: Sustainability Perspective

In an era with major developments in the energy sector, along with many benefits of energy consumption, it is also showing adverse effects on the end-users and the environment due to emission of various harmful gases mainly carbon dioxide (CO2). To deal with these issues, the zero energy building emerges to bring constructive developments through the construction industry. The concept of zero energy building is to develop a structural building which can generate its own required energy and have zero negative effects. The energy will be enough to fulfill all the requirements of the building operations and can save natural quarries. By increasing the numbers of zero energy buildings, major reforms can be brought in the construction industry and thus stabilizing the economy and the climate

Material Classification via Machine Learning Techniques: Construction Projects Progress Monitoring

Nowadays, the construction industry is on a fast track to adopting digital processes under the Industrial Revolution (IR) 4.0. The desire to automate maximum construction processes with less human interference has led the industry and research community to inclined towards artificial intelligence. This chapter has been themed on automated construction monitoring practices by adopting material classification via machine learning (ML) techniques. The study has been conducted by following the structure review approach to gain an understanding of the applications of ML techniques for construction progress assessment. Data were collected from the Web of Science (WoS) and Scopus databases, concluding 14 relevant studies. The literature review depicted the support vector machine (SVM) and artificial neural network (ANN) techniques as more effective than other ML techniques for material classification. The last section of this chapter includes a python-based ANN model for material classification. This ANN model has been tested for construction items (brick, wood, concrete block, and asphalt) for training and prediction. Moreover, the predictive ANN model results have been shared for the readers, along with the resources and open-source web links

Study of outcomes of Desarda repair in emergency conditions of inguinal hernia

Background There are two types of hernias in men and women: inguinal hernias and abdominal hernias. Inguinal hernias can be treated with the Desarda technique, a suture-based procedure that is becoming more popular. Objective: improving inguinal hernia repair outcomes by avoiding complications caused by foreign bodies.Patients and Methods: 40 male patients with difficult inguinal hernias were studied in the General Surgery Department of the Faculty of Medicine, Zagazig University Hospital, as part of a prospective study. Six months of follow-up took place from September 2020 to November 2021. Experienced and trained surgeons performed Desarda method procedures on patients. Pain and gait were measured at each follow-up.Results: Twenty-seven of the studied patients had no postoperative complications. Wound infection, seroma and scrotal edema occurred in 5, 6 and 2 of the patients respectively. A statistically significant difference in postoperative Visual Analogue Scale (VAS) scores was found between the groups tested (significantly higher among strangulated hernia). In terms of postoperative complications, the two groups analyzed differ significantly. In cases with obstructed hernia, non-complicated hernias accounted for 23, while strangulated hernias accounted for four. Conclusion: The Desarda approach appears to be a viable alternative to current practices. There are no problems or hernia recurrences as a result of this procedure, which is rapid, uncomplicated, and easy to learn and conduct

Value of serum tenascin-C in patients with acute myocardial infarction

Background: Myocardial infarction (MI) is defined as myocardial cell necrosis due to significant and sustained ischemia. TN-C is an extracellular matrix glycoprotein  that is expressed in several important steps during the very early stage of cardiogenesis. TN-C is not normally expressed in the adult heart, but transiently appears during pathological conditions and plays important roles in tissue remodeling.Aim: To study the role of TN-C in myocardial infarction patients and to evaluate its role as a predictor of HF in these patients.Methods: This study was conducted on 45 cases uniformly divided into 3 closely  matched (in age and sex) groups as follows: Group (I) includes 15 patients who were suffering from AMI; Group (II) includes 15 patients who were suffering from HF on top of MI; and Group (III) includes 15 healthy volunteers coming for regular annual checkup. 3–6 ml venous blood was collected on the day of admission under complete aseptic conditions and stored at 70 C until assayed by ELISA.Results: TN-C levels in the sera of patients with AMI Group (I) were significantly higher than those of healthy volunteers. Moreover, in Group I ofAMI, a positive  correlation between TN-C level on one side and CK, CK-MB and troponin T level on the other side was found. TN-C levels in the sera of patients with congestive heart failure on top of acute MI Group (II) were significantly higher than those of healthy volunteers. Pro-BNP levels in patients with heart failure Group (II) were significantlyhigher than those with AMI not complicated with heart failure Group (I). Levels of pro-BNP were also positively correlated with those of TN-C in patients with heart failure on top of AMI Group (II).Conclusions: Serum TN-C might be a novel marker reflecting active structural  remodeling in the myocardium following infarction, with high TN-C levels at acute stages possibly predicting progression of LV remodeling. Also, the incorporation of a combination of serum TN-C and plasma BNP levels may improve risk stratification for congestive heart failure after AMI. Further studies on large scale are needed for more evaluation of TN-C role in HF

Road Accident Data Collection Systems in Developing and Developed Countries: A Review

The road accidents trigger major financial loss and casualties to the individual as well as the state as a whole. The intelligent safety systems are developed to provide all road users with a safe transport system. This approach acknowledges the sensitivity of individuals to extreme injury in road accidents and recognizes the need for the system for improvement. To establish a proper system for road accident prevention, records from prior accidents play a key role in the evaluation and prediction of the accident, damage, and consequences. Therefore, this study was performed to evaluate and comparing existing practices in developing and developed countries for collecting road accident data. Moreover, the manual and digital approaches of data collection are highlighted. Keeping this in mind, this review provides an overview of how developing countries currently collect their data and their data dissemination methods to extract such useful information, which could prove beneficial in deciding the road safety programs for the well-being of end-users

Key Enablers of Resilient and Sustainable Construction Supply Chains: A Systems Thinking Approach

In the globalized world, one significant challenge for organizations is minimizing risk by building resilient supply chains (SCs). This is important to achieve a competitive advantage in an unpredictable and ever-changing environment. However, the key enablers of such resilient and sustainable supply chain management are less explored in construction projects. Therefore, the present research aims to determine the causality among the crucial drivers of resilient and sustainable supply chain management (RSSCM) in construction projects. Based on the literature review, 12 enablers of RSSCM were shortlisted. Using the systems thinking (ST) approach, this article portrays the interrelation between the 12 shortlisted resilience enablers crucial for sustainability in construction projects. The causality and interrelationships among identified enablers in the developed causal loop diagram (CLD) show their dynamic interactions and impacts within the RSSCM system. Based on the results of this study, agility, information sharing, strategic risk planning, corporate social responsibility, and visibility are the key enablers for the RSSCM. The findings of this research will enable the construction managers to compare different SCs while understanding how supply chain characteristics increase or decrease the durability and ultimately affect the exposure to risk in the construction SCs

A Bibliometric Review of Research Trends on Kenaf Fiber Reinforced Concrete

To prevent the excessive depletion of natural resources, sustainable development requires using alternate sustainable materials. Researchers in the field of advanced construction materials are increasingly paying attention to kenaf fibers as a "green" material because of their possible application in composites to advance sustainable development. However, there has been no attempt of scientometric analysis to investigate the comprehensive understanding of the present state of applications of kenaf fibers in reinforced concrete. The study aims to perform a bibliometric analysis of the existing kenaf fibers reinforced concrete literature and to provide a picture of the research status during the last ten years from 2013 to September 2022. There were 303 articles extracted from the Scopus database. The “VOSviewer” tool was employed to visualize the literature containing the most active scientific journals, countries, and highly used keywords in the field of fibers reinforced concrete. The outcomes showed that “Hybrid Composites”, “Impact Strength”, “Water Absorption”, “Scanning Electron Microscopy”, “Polypropylenes” and “Polymer Composite” have recently emerged as themes related to the applications of KFRC, and grabbed the interest of academics, may also offer future research opportunities. Additionally, according to the frequency of the keywords used, three important research domains associated with kenaf fibers within the concrete in the construction materials field have been identified, including “Mechanical Properties”, “Fiber Reinforced Plastics”, and “Tensile Strength”. Furthermore, the recent studies on the impact of kenaf fiber utilization on the structural performance of reinforced concrete are reviewed. Accordingly, the explanations related to research findings, suggestions for future studies have been provided on the incorporation of kenaf fibers reinforced concrete in civil engineering applications

Evaluation of In Vitro Antioxidant, Anti-Obesity, and Anti-Diabetic Activities of

Opuntia ficus cladodes (OFC) are considered one of the wastes that result from opuntia cultivation, and their disposal by traditional methods results in many environmental problems. Therefore, this study was conducted with two aims. The first was the production of OFC gel, and the evaluation of its in vitro antioxidant (by two methods, DPPH and ABTS), anti-obesity, and anti-diabetic activities. The second was an investigation of the effects of different concentrations of this gel (0, 50, and 100%) as an edible coating on the quality of shrimp during 8 days of refrigerated storage. The results showed that this gel was characterised by a high content of ash (10.42%), total carbohydrates (75.17%), and total phenols (19.79 mg GAE/g). OFC gel contained six types of sugars: arabinose, xylose, galactose, rhamnose, glucose, and uronic acid, and the most abundant was xylose (36.72%). It is also clear from the results that the OFC gel had high antioxidant properties, which were higher against DPPH than ABTS at the same concentration. OFC gel showed a high inhibition activity against lipase, α-glycosidase, and α-amylase enzymes, and their IC50 values were 1.43 mg/mL, 0.78 mg/mL, and 0.57 mg/mL, respectively. The results also stated that shrimp coated with OFC gel had lower pH, drip loss, TVB-N, and TBA values through the days of refrigerated storage. Moreover, the shrimp coated with 100% OFC gel were better than those coated with 50% OFC gel. In conclusion, OFC gel showed high potency as active antioxidant, for its enzyme anti-activities, and as an edible coating for shrimp